Consumers are increasingly using automated mechanisms to perform every day transactions. Kiosks exist to avoid enterprise personnel and lines. These automated kiosks allow consumers to perform transactions with an enterprise or agency with little to no human intervention. Individuals also perform transactions online and are capable of using their smart phones to check out of stores.
Consequently, information about a specific consumer and that consumer's preferences and habits are becoming harder and harder to ascertain. Recently, advancements have permitted a centralized consumer preference database. This allows preferences of any particular consumer to be captured from a variety of channels (in-person communication, cell communication, web communication, in-store communication, home phone communication, kiosk communication, and the like). Such advancement is significant because preferences of a consumer on one communication channel may different with that of another communication channel.
However, this centralized enterprise preference system is still not automatically tied or integrated with specific enterprise loyalty systems. This means that an entire 360 degree view of a consumer is not being captured and processed in a timely fashion when a specific consumer interacts with a specific enterprise and its loyalty applications.
As a result and for the most part, retailers providing consumer products and services currently rely on historical data from systems, such as: Customer Relationship Management (CRM), survey and transaction history to create and build offers and discounts to their consumers. These retailers presently need a means of capturing a “true voice” of customer and preference information across multiple channel/portals and being able to create those offers and discounts in real time. Further, enterprises need to be able leverage existing segmentation from their loyalty system and the centralized preference information together to create targeted offers in a real-time manner.
In particular, retailers typically interact with a large number of historical data systems and rely on customer research to create the conditions and logic to determine what triggers an offer, discount or promotion that is then provided to consumers. Retailers have not had a way for preference information from the consumer channels to feed into the loyalty system in real time such that the information is immediately usable as conditions for dynamic evaluation of offers, promotions and/or discounts.